We propose proper methods to impute the item nonresponse in 4-8-4 rotation sample survey. We consider nonignorable nonresponse mechanism that can happen when survey deals with sensitive question (e.g. income, labor force). We utilize modeling imputation method based on Bayesian approach to avoid a boundary solution problem. We also estimate a interview time bias using imputed data and calculate cell expectation and marginal probability on fixed time after removing estimated bias. We compare the mean squared errors and bias between maximum likelihood method and Bayesian methods using simulation studies.
Park, Jungsu;Baek, Jiwon;You, Kwangtae;Nam, Seung Won;Kim, Jongrack
Journal of Korean Society on Water Environment
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v.37
no.4
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pp.275-285
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2021
Algal bloom is an important issue in maintaining the safety of the drinking water supply system. Fast detection and classification of algae images are essential for the management of algal blooms. Conventional visual identification using a microscope is a labor-intensive and time-consuming method that often requires several hours to several days in order to obtain analysis results from field water samples. In recent decades, various deep learning algorithms have been developed and widely used in object detection studies. YOLO is a state-of-the-art deep learning algorithm. In this study the third version of the YOLO algorithm, namely, YOLOv3, was used to develop an algae image detection model. YOLOv3 is one of the most representative one-stage object detection algorithms with faster inference time, which is an important benefit of YOLO. A total of 1,114 algae images for 30 genera collected by microscope were used to develop the YOLOv3 algae image detection model. The algae images were divided into four groups with five, 10, 20, and 30 genera for training and testing the model. The mean average precision (mAP) was 81, 70, 52, and 41 for data sets with five, 10, 20, and 30 genera, respectively. The precision was higher than 0.8 for all four image groups. These results show the practical applicability of the deep learning algorithm, YOLOv3, for algae image detection.
Kim, Seo-Jun;Kim, Sang-Hyuk;Yoon, Byung-Man;Ji, Un
Journal of Korea Water Resources Association
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v.45
no.8
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pp.783-794
/
2012
The analysis for unsteady flow is necessary to design the hydraulic structures affected by water level and discharge changes through time. The numerical model has been generally used for unsteady flow analysis, however it is difficult to acquire field data to calibrate and validate the numerical model. Even though it is possible to collect field data for some case, high cost and labor are required and sometimes it is considered that the confidence of measured data is very low. In this case, the experimental data for unsteady flow can be used to calibrate and validate the numerical model as an alternative. Therefore, the discharge-supply system which could generate various type of unsteady flow hydrograph was developed in this study. Also, the accuracy of the unsteady flow hydrograph generated by developed dischargesupply system in the experiment was evaluated by comparing with target hydrograph. Accuracy errors and Root Mean Square Error (RMSE) were analyzed for the rectangular-type hydrograph with sudden changes of flow, triangular-type hydrograph with short peak time, and bell-type flood hydrograph. As a result, the generating error of the discharge-supply system for the rectangular-type hydrograph was about 59% which was maximum error among various types. Also, it was represented that RMSE for the triangular-type hydrographs with single and double peaks were approximately corresponding to 10%. However, RMSE for the bell-type flood hydrograph was lower than 2%.
This report is prepared to find how the filament of cocoon bave size deviation relates with the raw silk made by them which are intensively cultured in this country. Three recommended hybrid varieties and two varieties under working at Suwon Sericultural Experiment Station were selected as specimens. The cocoons were reeled as an individual filament of every fifty meters long skein with a wrap reel to weigh the denier and to investigate the relationship of the above statement so that it may be used for the quality estimation before processing it into raw silk. The conclusions obtained are as follows. (1) The variation of Pk${\times}$Sn was found as best cocoon for 21 denier raw silk use, but the number of cocoon to make the denier has to be eight which might cause more labor cost. (2) Baektoo-Kumkang and Myohiang-Chongchon were found as economical varieties for 21 denier use. (3) Seulak-Soyang is a proper variety for the use of 14 or 28 denier silk use. (4) Myohiang-Chongchon did not confirm a good property from the aspect of denier deviation. (5) It was found that there was a fairly strong corelationship between the mean cocoon bave size deviation as indicated by Ono's report. (6) Three graphs were prepared to estimate the cocoon quality before processing into various sizes of raw silk using the mean cocoon bave size and the raw silk size to be prepared. (7) Mean time, the graph which is able to estimate the expectable grade of the raw silk size deviation was designed for the practical use. (8) The expectable grade of the varieties used in this report were found as following data. Notice (A......cocoon number to make raw silk (B......total cocoon bave size deviation (C......expectable silk grade (9) The result of the work concerning the expectable denier deviation on 21 denier silk was the same with the statistical actual testing result as 1.25 D while the distribution showed farther necessity of improvement in technically.
Candida glabrata is the second most prevalent causative agent for candidiasis following C. albicans. The opportunistic yeast, C. glabrata, is able to cause the critical bloodstream infections in hospitalized patients. Conventional identification methods for yeasts are often time consuming and labor intensive. Therefore, recent studies on sequence-based identification have been conducted. Recently, sequencing the D1/D2 domain of the large subunit ribosomal RNA gene and the internal transcribed spacers (ITS) 1 and ITS2 regions of the ribosomal DNA has proven useful for DNA-based identification of most species of fungi. In the present study, therefore, fungal ITS and D1/D2 domain regions were targeted and analyzed by DNA sequencing for the accurate identification of C. glabrata clinical isolates. A total of 102 C. glabrata clinical isolates from various clinical samples including bloodstream, catheterized urine, bile and other body fluids were used in the study. The results of the DNA sequence analysis showed that the mean standard deviation of species identity percent score between ITS and D1/D2 domain regions was $97.8%{\pm}2.9$ and $99.7%{\pm}0.46$, respectively. These results revealed that the D1/D2 domain region might be a better target for identifying C. glabrata clinical isolates based on DNA sequences than the ITS1 and ITS2 regions. However, in order to evaluate the usefulness of D1/D2 domain region for species identification of all Candida species, other Candida species such as C. albicans, C. tropicalis, C. dubliniensis, and C. krusei should be verified in further studies additionally.
Eun-Sung, Park;Ajay Patel, Kumar;Muhammad Akbar Andi, Arief;Rahul, Joshi;Hongseok, Lee;Byoung-Kwan, Cho
Korean Journal of Agricultural Science
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v.49
no.3
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pp.483-493
/
2022
It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R2 of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.
The development of radish collectors has the potential to increase radish yields while decreasing the time and dependence on human labor in a variety of field activities. Stress and fatigue analyses are essential to ensure the optimal design and machine life of any agricultural machinery. The objectives of this research were to analyze the stress and fatigue of major components of a tractor-mounted radish collector under dynamic load conditions in an effort to increase the design dependability and dimensions of the materials. An experiment was conducted to measure the shaft torque of stem-cutting and transferring conveyor motors using rotary torque sensors at different tractor ground speeds with and without a load. The Smith-Watson-Topper mean stress equation and the rain-flow counting technique were utilized to determine the required shear stress with the distribution of the fatigue life cycle. The severity of the operation was assessed using Miner's theory. All running conditions produced more than 107 of high cycle fatigue strength. Furthermore, the highest severity levels for motor shafts used for stem cutting and transferring and for transportation joints and cutting blades were 2.20, 4.24, 2.07, and 1.07, and 1.97, 3.81, 1.73, and 1.07, respectively, with and without a load condition, except for 5.24 for a winch motor shaft under a load. The stress and fatigue analysis presented in this study can aid in the selection of the most appropriate design parameters and material sizes for the successful construction of a tractor-mounted radish collector, which is currently under development.
Proceedings of the Korean Society of Crop Science Conference
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2022.10a
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pp.132-132
/
2022
The application of direct seeding cultivation reduces time, labor, and cost. However, this application often has poor seedling establishment and leads to lower yield as compared to transplanting system. The tolerance to anaerobic and low temperature germination is important to improve seedling establishment and the wide-spread application of direct seeding method. This study was carried out to evaluate the responses of three japonica cultivars to different temperatures (15℃, 18℃, 21℃, 24℃, and 27℃) and different flooding levels (1 cm, 4 cm, 7 cm, 10 cm) during germination and seedling development. The mean survival percentage significantly increased (P<0.05) when the flooding level decreased and when temperature increased. There were significant effects of the interaction between temperature and water depth on survival percentage and seedling height. When temperature decreased from 27℃ to 15℃, the germination duration significantly increased from 6.4 days to 16.3 days while the germination speed, survival percentage, and seedling height decreased from 5.3 seeds day-1, 61.9% and 190.6 cm to 2.2 seeds day-1, 33.2%, and 47 cm, respectively. The increase in temperature under submergence condition was associated with the increased expression of Amy3D and ALDH2a but the decreased expression of ADH1 and PDC1. The results of this research would be used for further studies and breeding programs to improve rice seedling establishment and the application of direct seeding cultivation.
Journal of Information Science Theory and Practice
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v.11
no.4
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pp.51-81
/
2023
This study aimed to study its required performance requirements and proposes a competency framework necessary for the digital workforce of the Provincial Offices in Thailand. The specific primary informants were determined as 17 people. The collecting process was performed using the Delphi technique and the electronic Delphi technique in two phases, totaling four rounds. In the first time, a structured interview was used to conduct online interviews for 15 people. Content validation was performed to determine issues of the competency framework essential for the digital workforce with 7-level scaled questionnaires, and then online reviews were collected between 10-15 people (2nd to 4th times). A consensus was found and confirmed four times with descriptive statistics, namely frequency, mean, standard deviation, mode, median, and the absolute value of the difference between mode and median, interquartile range, and application of the conceptual framework. The research findings revealed that the essential competency requirements for the digital workforce were covered in digital literacy (six aspects), digital skills (four aspects), and digital characteristics (four aspects). Consensus was confirmed for 84 issues. Therefore, it was concluded that 61 points for building an essential competency framework for the digital workforce made them effective in using digital technology as a labor-saving instrument, as well as for expanding the breadth of development of digital expertise to include members of the organization's digital practitioner network. This development will benefit government agencies and the private sector, both national and international, in the future.
Selda Ciftci Inceoglu;Aylin Ayyildiz;Figen Yilmaz;Banu Kuran
Journal of Yeungnam Medical Science
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v.41
no.3
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pp.220-227
/
2024
Background: Electrodiagnostic testing (EDX) is important in the diagnosis and follow-up of neuropathic and myopathic diseases. This study aimed to demonstrate the compatibility between clinical prediagnosis and electrophysiological findings. Methods: EDX results from 2004 to 2020 at the physical medicine and rehabilitation (PM&R) clinic were screened. Tests with missing data, reevaluation studies, and cases of peripheral facial paralysis were excluded. The clinical prediagnosis and EDX results were recorded, and their compatibility was evaluated. Results: A total of 2,153 tests were included in this study. The mean age was 49.0±13.9 years and 1,533 of them (71.2%) were female. The most frequently referred clinic was the PM&R clinic (90.0%). Numbness (73.6%) was the most common complaint, followed by pain (15.3%) and weakness (13.9%). The most common prediagnosis was entrapment neuropathy (55.3%), radiculopathy (16.1%), and polyneuropathy (15.7%). Carpal tunnel syndrome was the most frequently identified type of entrapment neuropathy (78.3%). Six hundred and seventy EDX results (31.1%) were within normal limits. While the EDX results were consistent with the prediagnosis in 1,328 patients (61.7%), a pathology different from the prediagnosis was detected in 155 patients (7.2%). In the discrepancy group, the most common pathologies were entrapment neuropathy (51.7%), polyneuropathy (17.3%), and radiculopathy (15.1%). The most common neuropathy type was carpal tunnel syndrome (79.3%). Conclusion: After adequate anamnesis and physical and neurological examinations, requesting further appropriate tests will increase the prediagnosis accuracy and prevent unnecessary expenditure of time and labor.
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